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Predictivity of tourism demand data

journal contribution
posted on 2021-07-01, 00:00 authored by Yishuo ZhangYishuo Zhang, Gang LiGang Li, Birgit MUSKAT, Quan VuQuan Vu, Rob Law
As tourism researchers continue to search for solutions to determine the best possible forecasting performance, it is important to understand the maximum predictivity achieved by models, as well as how various data characteristics influence the maximum predictivity. Drawing on information theory, the predictivity of tourism demand data is quantitatively evaluated and beneficial for improving the performance of tourism demand forecasting. Empirical results from Hong Kong tourism demand data show that 1) the predictivity could largely help the researchers estimate the best possible forecasting performance and understand the influence of various data characteristics on the forecasting performance.; 2) the predictivity can be used to assess the short effect of external shock — such as SARS over tourism demand forecasting.

History

Journal

Annals of tourism research

Volume

89

Article number

103234

Pagination

1 - 16

Publisher

Elsevier

Location

Amsterdam, The Netherlands

eISSN

0160-7383

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

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